In digital printing, image data representing a pattern of colors to be printed is converted into a pattern of colorants that are applied to a receiver to form a printed image. Ideally, the image data is free of noise and the printed image has a pattern of colorants with the same colors as the pattern of colors from the image data. However, no printing system is ideal and printed images occasionally have areas with colors that deviate from the pattern of colors called for in the image data. In some cases, these deviations are intentional. In other cases, these deviations are unintentional. The latter deviations are known as noise.
Noise can be introduced during any of a number of printing and prepress activities and many common printing processes such as plate making, screening, color separation, half-tone processing have a potential to introduce some level of noise in a print. For example, in electrostatographic systems, some of the noise is associated with the use of toner, which is typically provided in a dry particulate form, then patterned, transferred to a receiver and fused to the receiver to form the print. In such electrostatographic systems, it has been known that curves of granularity number vs. screen resolution (lines per inch, “lpi”) are different with different toner particle sizes and with a uniform nominal toner particle size and different toner particle size distributions.
Noise can also exist in the image data provided for printing. This noise can arise at any stage in the process in which image data is generated for printing. For example such noise can arise during image capture, mastering, editing or compression.
Noise reduction algorithms and other techniques can be applied uniformly to all images, but this approach is inefficient, since some of the images may not benefit from noise reduction. In addition to allowing greater efficiency, variable noise reduction can produce better results. The application of a noise filter on an image often has an unintended consequence of reducing desirable image detail. Methods for designing and using Sigma filters are disclosed in U.S. Pat. No. 6,907,144 that attempt to minimize the loss of image detail while reducing the random noise present in a digital image. U.S. Pat. No. 5,923,775 (Snyder et al.) discloses varying noise reduction based on characteristics of an image. U.S. Pat. No. 6,934,421 (Gindele et al.) discloses varying noise reduction in accordance with the characteristics of a particular input source. U.S. Pat. No. 6,931,160 teaches use of a noise table in noise reduction. U.S. Pat. No. 7,065,255 (Chen et al.) discloses method and apparatus, in which noise in digital images is reduced using a noise table that is selected based on metadata associated with the respective images.
These efforts notwithstanding, noise continues to be evident in printed images and there remains an ongoing desire for additional methods and systems that can be used to further reduce noise.